Book Image

Data Analytics Made Easy

By : Andrea De Mauro
4 (1)
Book Image

Data Analytics Made Easy

4 (1)
By: Andrea De Mauro

Overview of this book

Data Analytics Made Easy is an accessible beginner’s guide for anyone working with data. The book interweaves four key elements: Data visualizations and storytelling – Tired of people not listening to you and ignoring your results? Don’t worry; chapters 7 and 8 show you how to enhance your presentations and engage with your managers and co-workers. Learn to create focused content with a well-structured story behind it to captivate your audience. Automating your data workflows – Improve your productivity by automating your data analysis. This book introduces you to the open-source platform, KNIME Analytics Platform. You’ll see how to use this no-code and free-to-use software to create a KNIME workflow of your data processes just by clicking and dragging components. Machine learning – Data Analytics Made Easy describes popular machine learning approaches in a simplified and visual way before implementing these machine learning models using KNIME. You’ll not only be able to understand data scientists’ machine learning models; you’ll be able to challenge them and build your own. Creating interactive dashboards – Follow the book’s simple methodology to create professional-looking dashboards using Microsoft Power BI, giving users the capability to slice and dice data and drill down into the results.
Table of Contents (14 chapters)
And now?
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What is Machine Learning?

Autonomous self-driving cars, ultraprecise robot surgeons, impeccable virtual assistants, fully automated financial traders: some of the most promising AI applications seem more like sci-fi material than prospects to an imminent reality. We could fill entire books by just collecting and presenting sensational stories of algorithmic wonders. If we manage—instead—to keep both feet firmly on the present ground and recognize how intelligent algorithms can already support our everyday work needs, then we start unlocking tangible value for us and our business. This is what this chapter is all about: stripping away the myth from reality by meeting in person the main machine learning algorithms and techniques. The end objective is to start counting on them as everyday companions rather than out-of-reach, futuristic possibilities.

In this chapter, we will find answers to the following questions:

  • What are AI and machine learning?
  • What is...